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Hi Stanislav and Martin,
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<div class="">Thank you both for your quick replies.
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<div class=""><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);" class="">Stanislav - </span>Regarding the saving of the data to binary. When I first tried running my model setup I wrote the array in one go similar to the way that you <font color="#000000" class=""><span style="caret-color: rgb(0, 0, 0);" class="">suggest
but hit the same problem. As a sanity check I've just run the model with new forcing files generated with the array written in one go </span></font><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);" class="">and I can confirm that I get the same
model behaviour.</span></div>
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</span></div>
<div class=""><font color="#000000" class="">I forgot to mention that I am starting the ocean with zero moment (I only define initial temperature and salinity), and so the 1500 years is so that my <span style="caret-color: rgb(0, 0, 0);" class="">simulation
approaches a state of</span> equilibrium. I look at the final 50 yr of climatology just to get a snapshot of the ocean state. I have begun testing with just running the model from rest for 20 year, and my problem is present by then, so I can confirm that it
persists through the entire length of the integration.</font></div>
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<div class=""><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);" class="">Martin- thanks for the heads up regarding these diagnostics. If I implement some of these into my model I should be able to get some insight into my problem. I will give this
a go. </span></div>
<div class=""><font color="#000000" class="">I’ll keep the forum updated</font></div>
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<div class=""><font color="#000000" class="">Cheers</font></div>
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<div class=""><font color="#000000" class="">Stephen</font></div>
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<blockquote type="cite" class="">
<div class="">On 18 May 2020, at 13:31, Martin Losch <<a href="mailto:Martin.Losch@awi.de" class="">Martin.Losch@awi.de</a>> wrote:</div>
<br class="Apple-interchange-newline">
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Hi Stephen,
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<div class="">Stanislav’s description of how to generate time dependent 2D forcing fields to be used and interpolated by pkg/exf is correct. I just want to add, that sometimes the forcing products (re-analysis data) have a different ordering with (i,j)=(1,1)
at the NW corner, but MITgcm/pkg/exf expects them at the SW corner of the domain.</div>
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<div class="">If you don’t want to use exf-interpolation, then you do the same as for bathymetry (I guess a (ni=6*96,nj=96) field) for each of nt time slices and also save them like that, i.e. before saving your field would have these dimension: interpolated_field(1:ni,1:nj,1:nt),
or if that’s too large for your memory you can also write 2D slices one after another to the same file. For the vector data (taux, tauy) it’s far more tricky, because the directions on the cube faces change from face to face, so using exf-interpolation is
recommended.</div>
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<div class="">Your second question:</div>
<div class="">
<blockquote type="cite" class="">2) Currently I have MITgcm output monthly means of ocean variables but to help me understand my problem, is it possible to have MITgcm write out the monthly averages of the Input Forcing Fields? (or at least the surface wind
vectors)</blockquote>
<div class="">Easy with the diagnostics package: in availabe_diagnostics.log, there’s a long list of EXF related fields that you can save at any frequency you like, e.g. I have this for specific configuration that uses EXF:</div>
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<font face="Courier" class=""><span style="font-size: 9px;" class="">------------------------------------------------------------------------------------<br class="">
Num |<-Name->|Levs| mate |<- code ->|<-- Units -->|<- Tile (max=80c) <br class="">
------------------------------------------------------------------------------------<br class="">
</span></font>
<div class=""><font face="Courier" class=""><span style="font-size: 9px;" class=""> 199 |EXFhs | 1 | |SM U1|W/m^2 |Sensible heat flux into ocean, >0 increases theta<br class="">
200 |EXFhl | 1 | |SM U1|W/m^2 |Latent heat flux into ocean, >0 increases theta<br class="">
201 |EXFlwnet| 1 | |SM U1|W/m^2 |Net upward longwave radiation, >0 decreases theta<br class="">
202 |EXFswnet| 1 | |SM U1|W/m^2 |Net upward shortwave radiation, >0 decreases theta<br class="">
203 |EXFlwdn | 1 | |SM U1|W/m^2 |Downward longwave radiation, >0 increases theta<br class="">
204 |EXFswdn | 1 | |SM U1|W/m^2 |Downward shortwave radiation, >0 increases theta<br class="">
205 |EXFqnet | 1 | |SM U1|W/m^2 |Net upward heat flux (turb+rad), >0 decreases theta<br class="">
206 |EXFtaux | 1 | |UU U1|N/m^2 |zonal surface wind stress, >0 increases uVel<br class="">
207 |EXFtauy | 1 | |VV U1|N/m^2 |meridional surface wind stress, >0 increases vVel<br class="">
208 |EXFuwind| 1 | |UM U1|m/s |zonal 10-m wind speed, >0 eastward<br class="">
209 |EXFvwind| 1 | |VM U1|m/s |meridional 10-m wind speed, >0 northward<br class="">
210 |EXFwspee| 1 | |SM U1|m/s |10-m wind speed modulus ( >= 0 )<br class="">
211 |EXFatemp| 1 | |SM U1|degK |surface (2-m) air temperature<br class="">
212 |EXFaqh | 1 | |SM U1|kg/kg |surface (2-m) specific humidity<br class="">
213 |EXFevap | 1 | |SM U1|m/s |evaporation, > 0 increases salinity<br class="">
214 |EXFpreci| 1 | |SM U1|m/s |precipitation, > 0 decreases salinity<br class="">
215 |EXFsnow | 1 | |SM U1|m/s |snow precipitation, > 0 decreases salinity<br class="">
216 |EXFempmr| 1 | |SM U1|m/s |net upward freshwater flux, > 0 increases salinity<br class="">
217 |EXFpress| 1 | |SM U1|N/m^2 |atmospheric pressure field<br class="">
218 |EXFroff | 1 | |SM U1|m/s |river runoff, > 0 decreases salinity<br class="">
219 |EXFroft | 1 | |SM U1|deg C |river runoff temperature<br class="">
220 |EXFsalfx| 1 | |SM U1|psu.kg/m^2/s |upward salt flux, > 0 decreases salinity<br class="">
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<div class="">I find this very useful in debugging forcing fields.</div>
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<div class="">I am wondering why your problem only appears in the last 50 years of 1500 year run, if you forcing is cycle and repeats every 20 years. It’s not clear what should go wrong after 1500/20 = 75 successful cycles where you don’t see any problems.</div>
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<div class="">Martin</div>
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<blockquote type="cite" class="">On 18. May 2020, at 13:16, Stanislav Martyanov <<a href="mailto:martyanov.sd@gmail.com" class="">martyanov.sd@gmail.com</a>> wrote:<br class="">
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Hello, Stephen!<br class="">
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When I create my EXF input data, I just write 2D XY fields of meteo forcing for each required variable sequentially for each time-step. Say, I have an array of 2m air temperature 't2m' prepared and stored in the matlab's current workspace and I want to write
it into a binary file for use in MITgcm exf package. If I use daily-mean fields and 1deg horizontal resolution of the forcing data, I have the array of 360x180x366 elements for an ordinary year and 360x180x367 for a leap year. The additional record (366th
or 367th) will be used for the internal time-interpolation implemented in the model when the model's time step in less than 24 hours. When such array is correctly prepared in matlab, I write it:<br class="">
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fout = fopen('exf_hourly_t2m.bin','wb','ieee-be');<br class="">
fwrite(fout,t2m,'float32');<br class="">
fclose(fout);<br class="">
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And so on for each variable..<br class="">
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Also, the corresponding parameters should be correctly set in data.exf and EXF_OPTIONS.h if you use spatial interpolation.<br class="">
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Regards, <br class="">
Stanislav Martyanov<br class="">
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пн, 18 мая 2020 г. в 13:44, Stephen Hunter [EAR] <<a href="mailto:S.Hunter@leeds.ac.uk" class="">S.Hunter@leeds.ac.uk</a>>:<br class="">
<br class="">
Firstly my apologies for the long query (my 2 questions are summarised at the bottom)<br class="">
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I have set up a CS96 model for a deep-time palaeo experiment. I am using 20 years of monthly surface climatology in a cyclical manner to run the model for 1500 years. The surface climatology is from a global high-resolution atmosphere-only model. I am using
Matlab to generate the MITgcm boundary conditions (bathymetry) and forcing files. I believe that I have MITgcm correctly set-up as I can run the model from these boundary conditions and forcing files for 1500 years without problems. Globally integrated temperature on
ocean levels comes into equilibrium and I see a drift in globally integrated salinity (as I expect as I haven’t implemented a river scheme yet).<br class="">
<br class="">
I generate my bathymetry binary on a CS96 grid using the lat-lon specification within the grid definitions. I am satisfied that this works as I expect because I can use the reverse of my regridding process to unwrap the MITgcm climatological average back to
a regular lat-lon grid and the imprinted land sea mask comes out as expected.<br class="">
<br class="">
Whilst the model is happy to run for 1500 years, the processed climatology from the final 50 years appears incorrect. Whilst the surface ocean temperature appears visually OK (latitudinal distribution of temperatures appears fine). It is when I look closer,
things appear to be wrong. For example when I look at the surface ocean currents I have a lot of diverging currents where I would expect zonal equatorial currents. I also don’t have flow through ocean gateways and channels. I do get some western boundary currents
and some upwelling, but these are inconsistent in some regions.<br class="">
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I suspect that this mishmash is because I am creating the Forcing binaries incorrectly. I would therefore like to check if I am creating them correctly. Here is a simplified account of what I am doing….<br class="">
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For each climatological field I generate a binary file for each year of monthly data. I do this in Matlab by building a vector of the data and then saving this as a float64 binary. Consider a year of climatological data is an array of size (360,180,12), in
which longitude runs from -179.5 to 179.5 in 1-degree cells, and latitude runs from 89.5 to -89.5 in 1-degree cells. I then create a vector from this array with the following recipe (simplified pseudo code):<br class="">
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vec=zeros(360*180*12,1);<br class="">
counter=1;<br class="">
for month=1:1:12<br class="">
for lat=180:-1:1 <br class="">
for lon=1:1:360<br class="">
vec(counter,1)=data(lon,lat,month)<br class="">
counter=counter+1<br class="">
end<br class="">
end<br class="">
end<br class="">
<br class="">
I then write vec to a 64 bit binary. With regards to CPP options for EXF I am using configuration A1,B3 but currently without runoff. In data.exf I define Ustress, Vstress, atemp, aqh, precip, wspeed, swdown and lwdown to be read in from yearly binary files
with lon0 and lat0 as -179.5 and -89.5. My non scalar fields are on slightly different grid but these are specified accordingly.<br class="">
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I cannot find a description of the ordering of cell data within binary forcing files for the EXF package. I have tried writing array data directly to binary file, transposing my input data, changing the ordering that I fill vec, but these appear wrong also.
I have tried to write my forcing data to the CS96 grid (like I do for bathymetry) but I didn’t know how to order the data wrt to the time dimension. I would prefer to have EXF read and interpolate my lat-lon climatology.<br class="">
<br class="">
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My questions are therefore:<br class="">
<br class="">
1) What is the ordering of the data within binary forcing files that EXF reads?<br class="">
2) Currently I have MITgcm output monthly means of ocean variables but to help me understand my problem, is it possible to have MITgcm write out the monthly averages of the Input Forcing Fields? (or at least the surface wind vectors)<br class="">
<br class="">
<br class="">
Kind regards<br class="">
Stephen<br class="">
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